Author

S. Subramanian

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Jul 2026

Models for minimalist RAG: B1ade 335M Embedding and 1B Parameter Small Language Models

B1ade, an efficient RAG architecture comprising two purpose-built components: a compact embedding model and a purpose-built SLM shows that strategic model composition and reward design suffice for resource-efficient RAG, without large-scale pretraining.

S. Subramanian, M. Gungor, Vikram Elango · arXiv.org · 1 citation

Preprint Jul 2026

Super Weights in LLMs and the Failure of Selective Training

It is established that parameter importance does not imply parameter trainability in isolation, and that effective fine-tuning relies on structured decompositions over entire layers rather than targeting individually important weights.

S. Subramanian, Adewale Akinfaderin, Akarsha Sehwag · 0 citations